text
stringlengths
0
59.1k
### Migration from Python Frameworks
If you're coming from Python, the concepts are similar but the implementation differs:
```python
# LangChain (Python)
from langchain.llms import OpenAI
from langchain.chains import LLMChain
from langchain.memory import ConversationBufferMemory
llm = OpenAI(temperature=0.7)
memory = ConversationBufferMemory()
chain = LLMChain(llm=llm, memory=memory)
```
```typescript
// VoltAgent (TypeScript) - typed approach
import { Agent } from "@voltagent/core";
import { VercelAIProvider } from "@voltagent/vercel-ai";
import { openai } from "@ai-sdk/openai";
const agent = new Agent({
name: "Assistant",
instructions: "Helpful assistant",
llm: new VercelAIProvider(),
model: openai("gpt-4o"),
// Memory automatic - no configuration needed
});
```
### Migration from Manual API Integration
```typescript
// Old approach - manual API calls
const response = await openai.chat.completions.create({
messages: [{ role: "user", content: userInput }],
tools: [
/* manual tool definitions */
],
// Manual memory management...
});
// With VoltAgent - framework handles everything
const response = await agent.generateText(userInput, {
userId: "user-123",
conversationId: "chat-1",
});
```
## Community & Ecosystem
Advantages of VoltAgent's TypeScript-first community:
### TypeScript-First Community
- **NPM packages** built specifically for VoltAgent
- **Learning resources** TypeScript-specific documentation
- **Support channels** Active community on Discord, GitHub Discussions
### Enterprise Features
- **Security & compliance** built-in
- **Performance monitoring** with VoltOps
- **Type-safe configurations** compile-time validation
### TypeScript Advantages
- **Developer productivity**: Faster development cycles
- **Code quality**: Fewer bugs, better maintainability
- **Team collaboration**: Better code reviews and onboarding
- **Ecosystem maturity**: Rich tooling and libraries
### Get Started Now
- **Try VoltAgent**: Build your first TypeScript AI agent
- **Join the community**: Connect with other TypeScript AI developers
- **Contribute**: Help shape the future of TypeScript AI development
VoltAgent offers an alternative designed for AI agent development in the TypeScript ecosystem.
<|endoftext|>
# source: VoltAgent__voltagent/website/blog/2025-06-03-vercel-ai-observability/index.md type: docs
---
title: LLM Observability for Vercel AI SDK
description: How to track your LLM Agents built with Vercel AI SDK?
slug: vercel-ai-llm-observability
image: https://cdn.voltagent.dev/2025-05-31-vercel-ai-observability/social.png
authors: omeraplak
---
import ZoomableMermaid from '@site/src/components/blog-widgets/ZoomableMermaid';
## VoltOps: Tracking LLM Agents built with Vercel AI SDK in Production
[Vercel AI SDK](https://ai-sdk.dev/docs/introduction/) is today one of the most popular tools to create AI agents. That SDK is so popular among developers because of its TypeScript-first approach and inclusion of such cutting-edge AI features like streaming, tool usage, and multi-modal support right out of the box.
We wrote about this [in our previous blog post](https://voltagent.dev/blog/vercel-ai-sdk/).
![Vercel AI SDK Integration](https://cdn.voltagent.dev/docs/vercel-ai-observability-demo/vercel-ai-demo-with-multi-agent.gif)